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ORCIDChandan K. Reddy
Person information
- affiliation: Virginia Tech, Department of Computer Science, Blacksburg, VA, USA
- affiliation (PhD): Cornell University, Ithaca, NY, USA
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2020 – today
- 2024
[j46]Hamid Ghaderi
, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian:
Discovery of generalizable TBI phenotypes using multivariate time-series clustering. Comput. Biol. Medicine 180: 108997 (2024)- [j45]Sindhu Tipirneni, Ming Zhu, Chandan K. Reddy:
StructCoder: Structure-Aware Transformer for Code Generation. ACM Trans. Knowl. Discov. Data 18(3): 70:1-70:20 (2024) - [j44]Chang Lu, Chandan K. Reddy, Ping Wang, Dong Nie, Yue Ning:
Multi-Label Clinical Time-Series Generation via Conditional GAN. IEEE Trans. Knowl. Data Eng. 36(4): 1728-1740 (2024) - [c111]Fanyou Wu, Weijie Xu, Chandan K. Reddy, Srinivasan Sengamedu:
Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation. ACL (Findings) 2024: 8012-8026 - [c110]Akshita Jha, Vinodkumar Prabhakaran, Remi Denton, Sarah Laszlo, Shachi Dave, Rida Qadri, Chandan K. Reddy, Sunipa Dev:
ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. ACL (1) 2024: 12333-12347 - [c109]Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, Amir Barati Farimani:
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training. ICLR 2024 - [c108]Yuan Ling, Shujing Dong, Yarong Feng, Zongyi Joe Liu, George Karypis, Chandan K. Reddy:
KDD workshop on Evaluation and Trustworthiness of Generative AI Models. KDD 2024: 6729-6730 - [c107]Nurendra Choudhary, Edward W. Huang, Karthik Subbian, Chandan K. Reddy:
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce. WWW (Companion Volume) 2024: 206-215 - [i58]Akshita Jha, Vinodkumar Prabhakaran, Remi Denton, Sarah Laszlo, Shachi Dave, Rida Qadri, Chandan K. Reddy, Sunipa Dev:
Beyond the Surface: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. CoRR abs/2401.06310 (2024) - [i57]Hamid Ghaderi, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian:
Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering. CoRR abs/2401.08002 (2024) - [i56]Nurendra Choudhary, Edward W. Huang, Karthik Subbian, Chandan K. Reddy:
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce. CoRR abs/2403.00923 (2024) - [i55]Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, Chandan K. Reddy:
LLM-SR: Scientific Equation Discovery via Programming with Large Language Models. CoRR abs/2404.18400 (2024) - [i54]Sindhu Tipirneni, Ravinarayana Adkathimar, Nurendra Choudhary, Gaurush Hiranandani, Rana Ali Amjad, Vassilis N. Ioannidis, Changhe Yuan, Chandan K. Reddy:
Context-Aware Clustering using Large Language Models. CoRR abs/2405.00988 (2024) - [i53]Nanxu Gong, Chandan K. Reddy, Wangyang Ying, Yanjie Fu:
Evolutionary Large Language Model for Automated Feature Transformation. CoRR abs/2405.16203 (2024) - [i52]Fanyou Wu, Weijie Xu, Chandan K. Reddy, Srinivasan H. Sengamedu:
Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation. CoRR abs/2406.03703 (2024) - [i51]Mehrdad Khatir, Chandan K. Reddy:
Concept Formation and Alignment in Language Models: Bridging Statistical Patterns in Latent Space to Concept Taxonomy. CoRR abs/2406.05315 (2024) - [i50]Nikhil Abhyankar, Vivek Gupta, Dan Roth, Chandan K. Reddy:
H-STAR: LLM-driven Hybrid SQL-Text Adaptive Reasoning on Tables. CoRR abs/2407.05952 (2024) - [i49]Hyeong Kyu Choi, Weijie Xu, Chi Xue, Stephanie Eckman, Chandan K. Reddy:
Mitigating Selection Bias with Node Pruning and Auxiliary Options. CoRR abs/2409.18857 (2024) - [i48]Taicheng Guo, Chaochun Liu, Hai Wang, Varun Mannam, Fang Wang, Xin Chen, Xiangliang Zhang, Chandan K. Reddy:
Knowledge Graph Enhanced Language Agents for Recommendation. CoRR abs/2410.19627 (2024) - 2023
- [j43]Hamid Ghaderi, Brandon Foreman, Amin Nayebi, Sindhu Tipirneni, Chandan K. Reddy, Vignesh Subbian:
A self-supervised learning-based approach to clustering multivariate time-series data with missing values (SLAC-Time): An application to TBI phenotyping. J. Biomed. Informatics 143: 104401 (2023) - [j42]Amin Nayebi, Sindhu Tipirneni, Chandan K. Reddy, Brandon Foreman, Vignesh Subbian:
WindowSHAP: An efficient framework for explaining time-series classifiers based on Shapley values. J. Biomed. Informatics 144: 104438 (2023) - [j41]Chang Lu, Chandan K. Reddy, Yue Ning:
Self-Supervised Graph Learning With Hyperbolic Embedding for Temporal Health Event Prediction. IEEE Trans. Cybern. 53(4): 2124-2136 (2023) - [j40]Akshita Jha, Vineeth Rakesh, Jaideep Chandrashekar, Adithya Samavedhi, Chandan K. Reddy:
Supervised Contrastive Learning for Interpretable Long-Form Document Matching. ACM Trans. Knowl. Discov. Data 17(2): 27:1-27:17 (2023) - [j39]Zibo Liu, Parshin Shojaee, Chandan K. Reddy:
Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting. Trans. Mach. Learn. Res. 2023 (2023) - [j38]Parshin Shojaee, Aneesh Jain, Sindhu Tipirneni, Chandan K. Reddy:
Execution-based Code Generation using Deep Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c106]Akshita Jha, Chandan K. Reddy:
CodeAttack: Code-Based Adversarial Attacks for Pre-trained Programming Language Models. AAAI 2023: 14892-14900 - [c105]Akshita Jha, Aida Mostafazadeh Davani, Chandan K. Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev:
SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models. ACL (1) 2023: 9851-9870 - [c104]Akshita Jha, Adithya Samavedhi, Vineeth Rakesh, Jaideep Chandrashekar, Chandan K. Reddy:
Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis. EACL (Findings) 2023: 2300-2310 - [c103]Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy:
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks. IJCAI 2023: 3875-3883 - [c102]Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy:
International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models. KDD 2023: 5868-5869 - [c101]Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy:
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach. NeurIPS 2023 - [c100]Chang Lu, Chandan K. Reddy, Ping Wang, Yue Ning:
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. NeurIPS 2023 - [c99]Parshin Shojaee, Kazem Meidani, Amir Barati Farimani, Chandan K. Reddy:
Transformer-based Planning for Symbolic Regression. NeurIPS 2023 - [i47]Parshin Shojaee, Aneesh Jain, Sindhu Tipirneni, Chandan K. Reddy:
Execution-based Code Generation using Deep Reinforcement Learning. CoRR abs/2301.13816 (2023) - [i46]Akshita Jha, Adithya Samavedhi, Vineeth Rakesh, Jaideep Chandrashekar, Chandan K. Reddy:
Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis. CoRR abs/2302.03765 (2023) - [i45]Hamid Ghaderi, Brandon Foreman, Amin Nayebi, Sindhu Tipirneni, Chandan K. Reddy, Vignesh Subbian:
A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to Traumatic Brain Injury Phenotyping. CoRR abs/2302.13457 (2023) - [i44]Parshin Shojaee, Kazem Meidani, Amir Barati Farimani, Chandan K. Reddy:
Transformer-based Planning for Symbolic Regression. CoRR abs/2303.06833 (2023) - [i43]Hamid Ghaderi, Brandon Foreman, Amin Nayebi, Sindhu Tipirneni, Chandan K. Reddy, Vignesh Subbian:
Identifying TBI Physiological States by Clustering of Multivariate Clinical Time-Series. CoRR abs/2303.13024 (2023) - [i42]Nurendra Choudhary, Chandan K. Reddy:
Complex Logical Reasoning over Knowledge Graphs using Large Language Models. CoRR abs/2305.01157 (2023) - [i41]Akshita Jha, Aida Mostafazadeh Davani, Chandan K. Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev:
SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models. CoRR abs/2305.11840 (2023) - [i40]Zibo Liu, Parshin Shojaee, Chandan K. Reddy:
Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting. CoRR abs/2305.18687 (2023) - [i39]Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, Amir Barati Farimani:
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training. CoRR abs/2310.02227 (2023) - [i38]Chang Lu, Chandan K. Reddy, Ping Wang, Yue Ning:
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. CoRR abs/2310.09672 (2023) - [i37]Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy:
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach. CoRR abs/2310.18918 (2023) - 2022
- [j37]Amirsina Torfi, Edward A. Fox, Chandan K. Reddy:
Differentially private synthetic medical data generation using convolutional GANs. Inf. Sci. 586: 485-500 (2022) - [j36]Nurendra Choudhary, Charu C. Aggarwal, Karthik Subbian, Chandan K. Reddy:
Self-supervised Short-text Modeling through Auxiliary Context Generation. ACM Trans. Intell. Syst. Technol. 13(3): 51:1-51:21 (2022) - [j35]Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy:
Corpus-level and Concept-based Explanations for Interpretable Document Classification. ACM Trans. Knowl. Discov. Data 16(3): 48:1-48:17 (2022) - [j34]Sindhu Tipirneni, Chandan K. Reddy:
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series. ACM Trans. Knowl. Discov. Data 16(6): 105:1-105:17 (2022) - [c98]Ming Zhu, Karthik Suresh, Chandan K. Reddy:
Multilingual Code Snippets Training for Program Translation. AAAI 2022: 11783-11790 - [c97]Khoa D. Doan, Sarkhan Badirli, Chandan K. Reddy:
Unified Energy-Based Generative Network for Supervised Image Hashing. ACCV (6) 2022: 527-543 - [c96]Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian:
An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury. AMIA 2022 - [c95]Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy:
Attention-based aspect reasoning for knowledge base question answering on clinical notes. BCB 2022: 10:1-10:6 - [c94]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy:
Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. KDD 2022: 2789-2799 - [c93]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy:
Hyperbolic Neural Networks: Theory, Architectures and Applications. KDD 2022: 4778-4779 - [c92]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
ANTHEM: Attentive Hyperbolic Entity Model for Product Search. WSDM 2022: 161-171 - [c91]Anoushka Vyas, Nurendra Choudhary, Mehrdad Khatir, Chandan K. Reddy:
GraphZoo: A Development Toolkit for Graph Neural Networks with Hyperbolic Geometries. WWW (Companion Volume) 2022: 184-188 - [c90]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [i36]Chang Lu, Chandan K. Reddy, Ping Wang, Dong Nie, Yue Ning:
Multi-Label Clinical Time-Series Generation via Conditional GAN. CoRR abs/2204.04797 (2022) - [i35]Akshita Jha, Chandan K. Reddy:
CodeAttack: Code-based Adversarial Attacks for Pre-Trained Programming Language Models. CoRR abs/2206.00052 (2022) - [i34]Nurendra Choudhary, Chandan K. Reddy:
Towards Scalable Hyperbolic Neural Networks using Taylor Series Approximations. CoRR abs/2206.03610 (2022) - [i33]Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy:
Pseudo-Poincaré: A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks. CoRR abs/2206.04285 (2022) - [i32]Sindhu Tipirneni, Ming Zhu, Chandan K. Reddy:
StructCoder: Structure-Aware Transformer for Code Generation. CoRR abs/2206.05239 (2022) - [i31]Chandan K. Reddy, Lluís Màrquez, Fran Valero, Nikhil Rao, Hugo Zaragoza, Sambaran Bandyopadhyay, Arnab Biswas, Anlu Xing, Karthik Subbian:
Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search. CoRR abs/2206.06588 (2022) - [i30]Ming Zhu, Aneesh Jain, Karthik Suresh, Roshan Ravindran, Sindhu Tipirneni, Chandan K. Reddy:
XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence. CoRR abs/2206.08474 (2022) - [i29]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy:
Text Enriched Sparse Hyperbolic Graph Convolutional Networks. CoRR abs/2207.02368 (2022) - [i28]Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian:
An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury. CoRR abs/2208.06717 (2022) - [i27]Amin Nayebi, Sindhu Tipirneni, Chandan K. Reddy, Brandon Foreman, Vignesh Subbian:
WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley Values. CoRR abs/2211.06507 (2022) - 2021
- [j33]Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Neural Abstractive Text Summarization with Sequence-to-Sequence Models. Trans. Data Sci. 2(1): 1:1-1:37 (2021) - [j32]Ping Wang, Tian Shi, Chandan K. Reddy:
A Novel Tensor-Based Temporal Multi-Task Survival Analysis Model. IEEE Trans. Knowl. Data Eng. 33(9): 3311-3322 (2021) - [c89]Tian Shi, Liuqing Li, Ping Wang, Chandan K. Reddy:
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection. AAAI 2021: 13815-13824 - [c88]Sutanay Choudhury, Khushbu Agarwal, Colby Ham, Pritam Mukherjee, Siyi Tang, Sindhu Tipirneni, Veysel Kocaman, Suzanne Tamang, Robert Rallo, Chandan K. Reddy:
Tracking the Evolution of COVID-19 via Temporal Comorbidity Analysis from Multi-Modal Data. AMIA 2021 - [c87]Amin Nayebi, Sindhu Tipirneni, Brandon Foreman, Jonathan J. Ratcliff, Chandan K. Reddy, Vignesh Subbian:
Recurrent Neural Network based Time-Series Modeling for Long-term Prognosis Following Acute Traumatic Brain Injury. AMIA 2021 - [c86]Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning:
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. IJCAI 2021: 3529-3535 - [c85]Sumeet Katariya, Nikhil Rao, Chandan K. Reddy:
Workshop on Data-Efficient Machine Learning (DeMaL). KDD 2021: 4135-4136 - [c84]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs. NeurIPS 2021: 23440-23451 - [c83]Khoa D. Doan, Saurav Manchanda, Suchismit Mahapatra, Chandan K. Reddy:
Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings. SIGIR 2021: 665-674 - [c82]Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed, Neal Mangaokar, Jiameng Pu, Mobin Javed, Chandan K. Reddy, Bimal Viswanath:
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification. USENIX Security Symposium 2021: 2255-2272 - [c81]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. WWW 2021: 1373-1384 - [c80]Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy:
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. WWW 2021: 2946-2957 - [i26]Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed, Neal Mangaokar, Jiameng Pu, Mobin Javed, Chandan K. Reddy, Bimal Viswanath:
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification. CoRR abs/2103.04264 (2021) - [i25]Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, Bimal Viswanath:
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models. CoRR abs/2104.02107 (2021) - [i24]Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning:
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. CoRR abs/2105.07542 (2021) - [i23]Chang Lu, Chandan K. Reddy, Yue Ning:
Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction. CoRR abs/2106.04751 (2021) - [i22]Sindhu Tipirneni, Chandan K. Reddy:
Self-supervised Transformer for Multivariate Clinical Time-Series with Missing Values. CoRR abs/2107.14293 (2021) - [i21]Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy:
Fair Representation Learning using Interpolation Enabled Disentanglement. CoRR abs/2108.00295 (2021) - [i20]Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy:
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes. CoRR abs/2108.00513 (2021) - [i19]Akshita Jha, Vineeth Rakesh, Jaideep Chandrashekar, Adithya Samavedhi, Chandan K. Reddy:
Supervised Contrastive Learning for Interpretable Long Document Comparison. CoRR abs/2108.09190 (2021) - [i18]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs. CoRR abs/2110.13522 (2021) - 2020
- [j31]Ting Hua, Chang-Tien Lu, Jaegul Choo, Chandan K. Reddy:
Probabilistic Topic Modeling for Comparative Analysis of Document Collections. ACM Trans. Knowl. Discov. Data 14(2): 24:1-24:27 (2020) - [j30]Sina Dabiri, Chang-Tien Lu, Kevin P. Heaslip, Chandan K. Reddy:
Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data. IEEE Trans. Knowl. Data Eng. 32(5): 1010-1023 (2020) - [j29]Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, Chandan K. Reddy:
Deep Reinforcement Learning for Sequence-to-Sequence Models. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2469-2489 (2020) - [c79]Ming Zhu, Busra Celikkaya, Parminder Bhatia, Chandan K. Reddy:
LATTE: Latent Type Modeling for Biomedical Entity Linking. AAAI 2020: 9757-9764 - [c78]Jiameng Pu, Neal Mangaokar, Bolun Wang, Chandan K. Reddy, Bimal Viswanath:
NoiseScope: Detecting Deepfake Images in a Blind Setting. ACSAC 2020: 913-927 - [c77]Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy:
Question Answering with Long Multiple-Span Answers. EMNLP (Findings) 2020: 3840-3849 - [c76]Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, Bimal Viswanath:
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models. EuroS&P 2020: 139-157 - [c75]Aman Ahuja, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms. WSDM 2020: 7-15 - [c74]Ping Wang, Tian Shi, Chandan K. Reddy:
Text-to-SQL Generation for Question Answering on Electronic Medical Records. WWW 2020: 350-361 - [c73]Khoa D. Doan, Chandan K. Reddy:
Efficient Implicit Unsupervised Text Hashing using Adversarial Autoencoder. WWW 2020: 684-694 - [i17]Khoa D. Doan, Amir Kimiyaie, Saurav Manchanda, Chandan K. Reddy:
Image Hashing by Minimizing Independent Relaxed Wasserstein Distance. CoRR abs/2003.00134 (2020) - [i16]Khoa D. Doan, Saurav Manchanda, Fengjiao Wang, S. Sathiya Keerthi, Avradeep Bhowmik, Chandan K. Reddy:
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space. CoRR abs/2003.11774 (2020) - [i15]Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy:
A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification. CoRR abs/2004.13003 (2020) - [i14]Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy:
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. CoRR abs/2007.11192 (2020) - [i13]Tian Shi, Liuqing Li, Ping Wang, Chandan K. Reddy:
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection. CoRR abs/2009.09107 (2020) - [i12]Tian Shi, Ping Wang, Chandan K. Reddy:
Deliberate Self-Attention Network with Uncertainty Estimation for Multi-Aspect Review Rating Prediction. CoRR abs/2009.09112 (2020) - [i11]Amirsina Torfi, Edward A. Fox, Chandan K. Reddy:
Differentially Private Synthetic Medical Data Generation using Convolutional GANs. CoRR abs/2012.11774 (2020) - [i10]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. CoRR abs/2012.13023 (2020)
2010 – 2019
- 2019
- [j28]Ping Wang, Yan Li, Chandan K. Reddy:
Machine Learning for Survival Analysis: A Survey. ACM Comput. Surv. 51(6): 110:1-110:36 (2019) - [c72]Tian Shi, Vineeth Rakesh, Suhang Wang, Chandan K. Reddy:
Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts. CIKM 2019: 2723-2731 - [c71]Khoa D. Doan, Pranjul Yadav, Chandan K. Reddy:
Adversarial Factorization Autoencoder for Look-alike Modeling. CIKM 2019: 2803-2812 - [c70]Dhruv Sharma, Zahil Shanis, Chandan K. Reddy, Samuel Gerber, Andinet Enquobahrie:
Active Learning Technique for Multimodal Brain Tumor Segmentation Using Limited Labeled Images. DART/MIL3ID@MICCAI 2019: 148-156 - [c69]Tian Shi, Ping Wang, Chandan K. Reddy:
LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization. NAACL-HLT (Demonstrations) 2019: 66-71 - [c68]Aman Ahuja, Ashish Baghudana, Wei Lu, Edward A. Fox, Chandan K. Reddy:
Spatio-Temporal Event Detection from Multiple Data Sources. PAKDD (1) 2019: 293-305 - [c67]Khoa D. Doan, Guolei Yang, Chandan K. Reddy:
An Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation. PAKDD (3) 2019: 346-358 - [c66]Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Deep Transfer Reinforcement Learning for Text Summarization. SDM 2019: 675-683 - [c65]Ming Zhu, Aman Ahuja, Wei Wei, Chandan K. Reddy:
A Hierarchical Attention Retrieval Model for Healthcare Question Answering. WWW 2019: 2472-2482 - [c64]Xuan Zhang, Zhilei Qiao, Aman Ahuja, Weiguo Fan, Edward A. Fox, Chandan K. Reddy:
Discovering Product Defects and Solutions from Online User Generated Contents. WWW 2019: 3441-3447 - [i9]Tian Shi, Ping Wang, Chandan K. Reddy:
LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization. CoRR abs/1906.01512 (2019) - [i8]Ping Wang, Tian Shi, Chandan K. Reddy:
A Translate-Edit Model for Natural Language Question to SQL Query Generation on Multi-relational Healthcare Data. CoRR abs/1908.01839 (2019) - [i7]Ming Zhu, Busra Celikkaya, Parminder Bhatia, Chandan K. Reddy:
LATTE: Latent Type Modeling for Biomedical Entity Linking. CoRR abs/1911.09787 (2019) - 2018
- [j27]Sangho Suh, Sungbok Shin, Joonseok Lee, Chandan K. Reddy, Jaegul Choo:
Localized user-driven topic discovery via boosted ensemble of nonnegative matrix factorization. Knowl. Inf. Syst. 56(3): 503-531 (2018) - [j26]Vachik S. Dave, Mohammad Al Hasan, Baichuan Zhang, Chandan K. Reddy:
Predicting interval time for reciprocal link creation using survival analysis. Soc. Netw. Anal. Min. 8(1): 16 (2018) - [c63]Guolei Yang, Ying Cai, Chandan K. Reddy:
Recurrent Spatio-Temporal Point Process for Check-in Time Prediction. CIKM 2018: 2203-2211 - [c62]Guolei Yang, Ying Cai, Chandan K. Reddy:
Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis. IJCAI 2018: 2976-2983 - [c61]Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, Naren Ramakrishnan:
Social Media based Simulation Models for Understanding Disease Dynamics. IJCAI 2018: 3797-3804 - [c60]Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. SDM 2018: 99-107 - [c59]Tian Shi, Kyeongpil Kang, Jaegul Choo, Chandan K. Reddy:
Short-Text Topic Modeling via Non-negative Matrix Factorization Enriched with Local Word-Context Correlations. WWW 2018: 1105-1114 - [c58]Vineeth Rakesh, Weicong Ding, Aman Ahuja, Nikhil Rao, Yifan Sun, Chandan K. Reddy:
A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews. WWW 2018: 1573-1582 - [i6]Mahmudur Rahman, Tanay Kumar Saha, Mohammad Al Hasan, Kevin S. Xu, Chandan K. Reddy:
DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks. CoRR abs/1804.05755 (2018) - [i5]Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, Chandan K. Reddy:
Deep Reinforcement Learning For Sequence to Sequence Models. CoRR abs/1805.09461 (2018) - [i4]Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Deep Transfer Reinforcement Learning for Text Summarization. CoRR abs/1810.06667 (2018) - [i3]Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
Neural Abstractive Text Summarization with Sequence-to-Sequence Models. CoRR abs/1812.02303 (2018) - 2017
- [j25]Bhanukiran Vinzamuri, Yan Li, Chandan K. Reddy:
Pre-Processing Censored Survival Data Using Inverse Covariance Matrix Based Calibration. IEEE Trans. Knowl. Data Eng. 29(10): 2111-2124 (2017) - [c57]Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, Haesun Park:
PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering. AAAI 2017: 1001-1009 - [c56]Abhishek Sengupta, A. P. Prathosh, Satya Narayan Shukla, Vaibhav Rajan, Chandan K. Reddy:
Prediction and imputation in irregularly sampled clinical time series data using hierarchical linear dynamical models. EMBC 2017: 3660-3663 - [c55]Aman Ahuja, Wei Wei, Wei Lu, Kathleen M. Carley, Chandan K. Reddy:
A Probabilistic Geographical Aspect-Opinion Model for Geo-Tagged Microblogs. ICDM 2017: 721-726 - [c54]Vachik S. Dave, Mohammad Al Hasan, Chandan K. Reddy:
How Fast Will You Get a Response? Predicting Interval Time for Reciprocal Link Creation. ICWSM 2017: 508-511 - [c53]Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan K. Reddy:
Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization. IJCAI 2017: 4944-4948 - [c52]Vineeth Rakesh, Niranjan Jadhav, Alexander Kotov, Chandan K. Reddy:
Probabilistic Social Sequential Model for Tour Recommendation. WSDM 2017: 631-640 - [i2]Ping Wang, Yan Li, Chandan K. Reddy:
Machine Learning for Survival Analysis: A Survey. CoRR abs/1708.04649 (2017) - 2016
- [j24]Vijay Huddar, Bapu Koundinya Desiraju, Vaibhav Rajan, Sakyajit Bhattacharya, Shourya Roy, Chandan K. Reddy:
Predicting Complications in Critical Care Using Heterogeneous Clinical Data. IEEE Access 4: 7988-8001 (2016) - [j23]Yan Li, Changxin Bai, Chandan K. Reddy:
A distributed ensemble approach for mining healthcare data under privacy constraints. Inf. Sci. 330: 245-259 (2016) - [j22]Samir Al-Stouhi, Chandan K. Reddy:
Transfer learning for class imbalance problems with inadequate data. Knowl. Inf. Syst. 48(1): 201-228 (2016) - [j21]Jayanta K. Dutta, Bonny Banerjee, Chandan K. Reddy:
RODS: Rarity based Outlier Detection in a Sparse Coding Framework. IEEE Trans. Knowl. Data Eng. 28(2): 483-495 (2016) - [j20]Mahtab Jahanbani Fard, Ping Wang, Sanjay Chawla, Chandan K. Reddy:
A Bayesian Perspective on Early Stage Event Prediction in Longitudinal Data. IEEE Trans. Knowl. Data Eng. 28(12): 3126-3139 (2016) - [c51]Sattar Ameri, Mahtab Jahanbani Fard, Ratna Babu Chinnam, Chandan K. Reddy:
Survival Analysis based Framework for Early Prediction of Student Dropouts. CIKM 2016: 903-912 - [c50]Ping Wang, Karthik K. Padthe, Bhanukiran Vinzamuri, Chandan K. Reddy:
CRISP: Consensus Regularized Selection based Prediction. CIKM 2016: 1019-1028 - [c49]Yan Li, Lu Wang, Jie Wang, Jieping Ye, Chandan K. Reddy:
Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. ICDM 2016: 231-240 - [c48]Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan K. Reddy:
L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization. ICDM 2016: 479-488 - [c47]Bhanukiran Vinzamuri, Karthik K. Padthe, Chandan K. Reddy:
Feature Grouping Using Weighted l1 Norm for High-Dimensional Data. ICDM 2016: 1233-1238 - [c46]Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy:
A Multi-Task Learning Formulation for Survival Analysis. KDD 2016: 1715-1724 - [c45]Mahtab Jahanbani Fard, Sanjay Chawla, Chandan K. Reddy:
Early-Stage Event Prediction for Longitudinal Data. PAKDD (1) 2016: 139-151 - [c44]Yan Li, Bhanukiran Vinzamuri, Chandan K. Reddy:
Regularized Weighted Linear Regression for High-dimensional Censored Data. SDM 2016: 45-53 - [c43]Yan Li, Kevin S. Xu, Chandan K. Reddy:
Regularized Parametric Regression for High-dimensional Survival Analysis. SDM 2016: 765-773 - [c42]Yan Li, Vineeth Rakesh, Chandan K. Reddy:
Project Success Prediction in Crowdfunding Environments. WSDM 2016: 247-256 - [c41]Vineeth Rakesh, Wang-Chien Lee, Chandan K. Reddy:
Probabilistic Group Recommendation Model for Crowdfunding Domains. WSDM 2016: 257-266 - 2015
- [j19]Yan Li, Bhanukiran Vinzamuri, Chandan K. Reddy:
Constrained elastic net based knowledge transfer for healthcare information exchange. Data Min. Knowl. Discov. 29(4): 1094-1112 (2015) - [j18]Jaegul Choo, Changhyun Lee, Chandan K. Reddy, Haesun Park:
Weakly supervised nonnegative matrix factorization for user-driven clustering. Data Min. Knowl. Discov. 29(6): 1598-1621 (2015) - [j17]Chandan K. Reddy, Mohammad S. Aziz:
Predicting gene functions from multiple biological sources using novel ensemble methods. Int. J. Data Min. Bioinform. 12(2): 184-206 (2015) - [j16]Hannah Kim, Jaegul Choo, Chandan K. Reddy, Haesun Park:
Doubly supervised embedding based on class labels and intrinsic clusters for high-dimensional data visualization. Neurocomputing 150: 570-582 (2015) - [j15]Dilpreet Singh, Chandan K. Reddy:
A survey on platforms for big data analytics. J. Big Data 2: 8 (2015) - [j14]Faris Alqadah, Chandan K. Reddy, Junling Hu, Hatim F. Alqadah:
Biclustering neighborhood-based collaborative filtering method for top-n recommender systems. Knowl. Inf. Syst. 44(2): 475-491 (2015) - [c40]Alexander Kotov, Vineeth Rakesh, Eugene Agichtein, Chandan K. Reddy:
Geographical Latent Variable Models for Microblog Retrieval. ECIR 2015: 635-647 - [c39]Vineeth Rakesh, Jaegul Choo, Chandan K. Reddy:
Project Recommendation Using Heterogeneous Traits in Crowdfunding. ICWSM 2015: 337-346 - [c38]Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, Haesun Park:
Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization. KDD 2015: 567-576 - [p7]Chandan K. Reddy, Charu C. Aggarwal:
An Introduction to Healthcare Data Analytics. Healthcare Data Analytics 2015: 1-18 - [p6]Rajiur Rahman, Chandan K. Reddy:
Electronic Health Records: A Survey. Healthcare Data Analytics 2015: 21-59 - [p5]Chandan K. Reddy, Yan Li:
A Review of Clinical Prediction Models. Healthcare Data Analytics 2015: 343-378 - [p4]Martin Alther, Chandan K. Reddy:
Clinical Decision Support Systems. Healthcare Data Analytics 2015: 625-656 - [e2]Chandan K. Reddy, Charu C. Aggarwal:
Healthcare Data Analytics. Chapman and Hall/CRC 2015, ISBN 978-1-4822-3211-0 [contents] - 2014
- [j13]Omar Odibat, Chandan K. Reddy:
Efficient mining of discriminative co-clusters from gene expression data. Knowl. Inf. Syst. 41(3): 667-696 (2014) - [c37]Bhanukiran Vinzamuri, Yan Li, Chandan K. Reddy:
Active Learning based Survival Regression for Censored Data. CIKM 2014: 241-250 - [c36]Vineeth Rakesh, Dilpreet Singh, Bhanukiran Vinzamuri, Chandan K. Reddy:
Personalized Recommendation of Twitter Lists using Content and Network Information. ICWSM 2014 - [c35]Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Chandan K. Reddy, Barry L. Drake, Haesun Park:
PIVE: Per-Iteration visualization environment for supporting real-time interactions with computational methods. IEEE VAST 2014: 241-242 - [c34]Samir Al-Stouhi, Chandan K. Reddy:
Multi-Task Clustering using Constrained Symmetric Non-Negative Matrix Factorization. SDM 2014: 785-793 - [e1]Charu C. Aggarwal, Chandan K. Reddy:
Data Clustering: Algorithms and Applications. CRC Press 2014, ISBN 978-1-46-655821-2 [contents] - 2013
- [j12]Asfar S. Azmi, Aliccia Bollig-Fischer, Bin Bao, Bum-Joon Park, Sun-Hye Lee, Gyu Yong-Song, Gregory Dyson, Chandan K. Reddy, Fazlul H. Sarkar, Ramzi M. Mohammad:
Systems analysis reveals a transcriptional reversal of the mesenchymal phenotype induced by SNAIL-inhibitor GN-25. BMC Syst. Biol. 7: 85 (2013) - [j11]Chandan K. Reddy, Cristopher C. Yang:
Introduction to the special section on intelligent systems for health informatics. ACM Trans. Intell. Syst. Technol. 4(4): 62:1-62:3 (2013) - [j10]Jaegul Choo, Changhyun Lee, Chandan K. Reddy, Haesun Park:
UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization. IEEE Trans. Vis. Comput. Graph. 19(12): 1992-2001 (2013) - [c33]Vineeth Rakesh, Chandan K. Reddy, Dilpreet Singh, Ramachandran M. S.:
Location-specific tweet detection and topic summarization in Twitter. ASONAM 2013: 1441-1444 - [c32]Bhanukiran Vinzamuri, Chandan K. Reddy:
Cox Regression with Correlation Based Regularization for Electronic Health Records. ICDM 2013: 757-766 - [c31]Jimeng Sun, Chandan K. Reddy:
Big data analytics for healthcare. KDD 2013: 1525 - [p3]Chandan K. Reddy, Bhanukiran Vinzamuri:
A Survey of Partitional and Hierarchical Clustering Algorithms. Data Clustering: Algorithms and Applications 2013: 87-110 - [p2]Chandan K. Reddy, Mohammad Al Hasan, Mohammed J. Zaki:
Clustering Biological Data. Data Clustering: Algorithms and Applications 2013: 381-414 - [p1]Charu C. Aggarwal, Chandan K. Reddy:
Educational and Software Resources for Data Clustering. Data Clustering: Algorithms and Applications 2013: 607-616 - 2012
- [j9]Gerard Miller, Melissa Weatherwax, Timothy Gardinier, Naoki Abe, Prem Melville, Cezar Pendus, David L. Jensen, Chandan K. Reddy, Vince P. Thomas, James J. Bennett, Gary F. Anderson, Brent R. Cooley:
Tax Collections Optimization for New York State. Interfaces 42(1): 74-84 (2012) - [j8]Omar Odibat, Chandan K. Reddy:
Ranking differential Hubs in gene Co-Expression Networks. J. Bioinform. Comput. Biol. 10(1) (2012) - [j7]Indranil Palit, Chandan K. Reddy:
Scalable and Parallel Boosting with MapReduce. IEEE Trans. Knowl. Data Eng. 24(10): 1904-1916 (2012) - [c30]Samir Al-Stouhi, Chandan K. Reddy, David E. Lanfear:
Label Space Transfer Learning. ICTAI 2012: 727-734 - [c29]Noor Alaydie, Chandan K. Reddy, Farshad Fotouhi:
Exploiting Label Dependency for Hierarchical Multi-label Classification. PAKDD (1) 2012: 294-305 - [c28]Faris Alqadah, Joel S. Bader, Rajul Anand, Chandan K. Reddy:
Query-based Biclustering using Formal Concept Analysis. SDM 2012: 648-659 - 2011
- [j6]Chandan K. Reddy, Jin Hyeong Park:
Multi-resolution boosting for classification and regression problems. Knowl. Inf. Syst. 29(2): 435-456 (2011) - [c27]Omar Odibat, Chandan K. Reddy:
Ranking differential genes in co-expression networks. BCB 2011: 350-354 - [c26]Noor Alaydie, Chandan K. Reddy, Farshad Fotouhi:
A Bayesian integration model for improved gene functional inference from heterogeneous data sources. BCB 2011: 376-380 - [c25]Rajul Anand, Chandan K. Reddy:
Graph-Based Clustering with Constraints. PAKDD (2) 2011: 51-62 - [c24]Samir Al-Stouhi, Chandan K. Reddy:
Adaptive Boosting for Transfer Learning Using Dynamic Updates. ECML/PKDD (1) 2011: 60-75 - [c23]Rajul Anand, Chandan K. Reddy:
Constrained Logistic Regression for Discriminative Pattern Mining. ECML/PKDD (1) 2011: 92-107 - [c22]Omar Odibat, Chandan K. Reddy:
A Generalized Framework for Mining Arbitrarily Positioned Overlapping Co-clusters. SDM 2011: 343-354 - 2010
- [j5]Chandan K. Reddy, Bala Rajaratnam:
Learning mixture models via component-wise parameter smoothing. Comput. Stat. Data Anal. 54(3): 732-749 (2010) - [j4]Chandan K. Reddy, Mohammad S. Aziz:
Modeling local nonlinear correlations using subspace principal curves. Stat. Anal. Data Min. 3(5): 332-349 (2010) - [c21]Omar Odibat, Chandan K. Reddy, Craig N. Giroux:
Differential biclustering for gene expression analysis. BCB 2010: 275-284 - [c20]Mohammad S. Aziz, Chandan K. Reddy:
Robust prediction from multiple heterogeneous data sources with partial information. CIKM 2010: 1857-1860 - [c19]Noor Alaydie, Farshad Fotouhi, Chandan K. Reddy, Hamid Soltanian-Zadeh:
Noise and Outlier Filtering in Heterogeneous Medical Data Sources. DEXA Workshops 2010: 115-119 - [c18]Indranil Palit, Chandan K. Reddy:
Parallelized Boosting with Map-Reduce. ICDM Workshops 2010: 1346-1353 - [c17]Naoki Abe, Prem Melville, Cezar Pendus, Chandan K. Reddy, David L. Jensen, Vince P. Thomas, James J. Bennett, Gary F. Anderson, Brent R. Cooley, Melissa Kowalczyk, Mark Domick, Timothy Gardinier:
Optimizing debt collections using constrained reinforcement learning. KDD 2010: 75-84 - [c16]Mohammad S. Aziz, Chandan K. Reddy:
A Robust Seedless Algorithm for Correlation Clustering. PAKDD (1) 2010: 28-37 - [c15]Jaegul Choo, Chandan K. Reddy, Hanseung Lee, Haesun Park:
p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics. SDM 2010: 502-513
2000 – 2009
- 2009
- [c14]Indranil Palit, Chandan K. Reddy, Kendra L. Schwartz:
Differential Predictive Modeling for Racial Disparities in Breast Cancer. BIBM 2009: 239-245 - [c13]Chandan K. Reddy, Jin Hyeong Park:
Multi-resolution Boosting for Classification and Regression Problems. PAKDD 2009: 196-207 - [c12]Snehal Pokharkar, Chandan K. Reddy:
Identifying Information-Rich Subspace Trends in High-Dimensional Data. SDM 2009: 557-568 - [r1]Chandan K. Reddy, Bala Rajaratnam:
Theory and Practice of Expectation Maximization (EM) Algorithm. Encyclopedia of Data Warehousing and Mining 2009: 1966-1973 - 2008
- [j3]Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam:
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 30(7): 1146-1157 (2008) - [c11]Chandan K. Reddy, Fahima A. Bhuyan:
Retrieval and ranking of biomedical images using boosted haar features. BIBE 2008: 1-6 - [c10]Yazhene Krishnaraj, Chandan K. Reddy:
Boosting Methods for Protein Fold Recognition: An Empirical Comparison. BIBM 2008: 393-396 - [c9]Chandan K. Reddy, Bala Rajaratnam:
Component-wise parameter smoothing for learning mixture models. ICPR 2008: 1-4 - [c8]Chandan K. Reddy, Snehal Pokharkar, Tin Kam Ho:
Generating hypotheses of trends in high-dimensional data skeletons. IEEE VAST 2008: 139-146 - [c7]Chandan K. Reddy, Jin Hyeong Park:
Scale-Space Kernels for Additive Modeling. SSPR/SPR 2008: 714-723 - 2007
- [c6]Jin Hyeong Park, Chandan K. Reddy:
Scale-Space Based Weak Regressors for Boosting. ECML 2007: 666-673 - [c5]Hsiao-Dong Chiang, Chandan K. Reddy:
TRUST-TECH Based Neural Network Training. IJCNN 2007: 90-95 - [c4]Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset:
Looking for Great Ideas: Analyzing the Innovation Jam. WebKDD/SNA-KDD 2007: 21-39 - [i1]Chandan K. Reddy:
TRUST-TECH based Methods for Optimization and Learning. CoRR abs/0712.4126 (2007) - 2006
- [j2]Chandan K. Reddy, Yao-Chung Weng, Hsiao-Dong Chiang:
Refining motifs by improving information content scores using neighborhood profile search. Algorithms Mol. Biol. 1 (2006) - [j1]Chandan K. Reddy, Hsiao-Dong Chiang:
A Stability Boundary Based Method for Finding Saddle Points on Potential Energy Surfaces. J. Comput. Biol. 13(3): 745-766 (2006) - [c3]Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam:
Stability Region Based Expectation Maximization for Model-based Clustering. ICDM 2006: 522-531 - 2005
- [c2]Chandan K. Reddy, Hsiao-Dong Chiang:
Finding saddle points using stability boundaries. SAC 2005: 212-213 - 2004
- [c1]Chandan K. Reddy, George C. Stockman, Jannick P. Rolland, Frank A. Biocca:
Mobile Face Capture for Virtual Face Videos. CVPR Workshops 2004: 77
Coauthor Index
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